As shown in FIG. 1a, a sequence of video images is composed of successive images, some of these images, denoted I images, being encoded in Intraframe mode, either without reference to the past represented by the previous images of this sequence of images, or in Interframe mode, denoted P images, then a new I image, and so on.
It will be recalled that the predictive encoding of the P images makes it possible to reduce substantially the volume of encoded data, while retaining a reasonable encoding complexity.
On the assumption that, due to processing requirements at decoding for example, it is desired to access a specific image having a defined rank in the video stream, and in the sequence of video images, it is then necessary to decode the set of P images preceding this image, until reaching the previous I image. Any I image is in fact by definition autonomous from the encoding point of view, since the encoding of the latter, which is not predictive, does not call on the content of any previous image.
In order to reduce or minimize the access time to an image of a determined rank, it is common, during the process of encoding video image sequences, to insert one I image every second, in the case of standard video encoding of films for example. In this situation, a maximum decoding requirement of no more than 25 images is assured, in the case of a video image stream of 25 images per second, in order to access any image whatever from the above-mentioned stream.
In these conditions, a stream of video images or video image sequences is called random access when any image is accessible within a technically acceptable timeframe. If on the contrary, no I images inserted into the video image stream or sequence, which can technically be envisaged, the stream cannot be regarded as random access, as the access to the content of any image of a determined rank theoretically depends on all the previous images.
At the present time, the encoding of constant-flow video streams or sequences is carried out on the basis of processes known from the prior art, as shown in FIG. 1b. 
This process can consist of choosing a determined quantization step Q, from which it is estimated a priori that the latter will produce the desired image size.
Within the framework of severe constraints on the video stream or sequence, typically taking account of a very small encoded image buffer memory size at the level of the encoders or some commercially available decoders for example, the above-mentioned processes usually operate on the principle of a double iterative loop.
A first loop, shown in FIG. 1b, operates at the time level of the succession of images by:
1) allocating a target size Tc for the encoding of the current image, Fk, k referencing the rank of the image, this estimated size being in relation to the current fullness status of the buffer memory of the encoder;
2) determining the quantization step Q applied according to the characteristics of the current image to be encoded, in particular its complexity C, and a computational model M linking the quantization step Q to the estimated size {circumflex over (T)} and the complexity C of the image.
The computational model linking the estimated size {circumflex over (T)} to the quantization step Q and the complexity C is applied by imposing {circumflex over (T)}=Tc in order to find Q.
3) actual encoding of the current image Fk by applying the quantization step Q;
4) updating the computational model M according to the actual size T of the current encoded image.
A second iterative loop applied at the spatial level of the current image Fk, the latter being divided into encoding blocks Bj, j denoting the rank of the block in the image to be encoded, makes it possible to determine the quantization step Qj to be applied to the considered block Bj, in order to strictly comply with the imposed bit rate constraint.
The second above-mentioned loop can operate in a similar fashion to the one shown in FIG. 1b, and therefore is not shown in the drawing. It is possible thereby for each block Bj of the current image to determine the quantization step Qj applicable to the latter as a function of its complexity Cj, the model M being adapted once the block Bj has been encoded.
The second above-mentioned loop allows a much stricter compliance with the bit rate constraint or set value. For a more detailed description of the above mentioned processes, reference can usefully be made to the text of the standard MPEG4: ISO/IEC 14496-2 Information Technology—Coding of audio visual objects—Part 2: Visual, Annexe L.
Due to the absence of predictive encoding, the I images, other factors being equal, occupy considerably more space than a P image. Within the framework of the standard H.264 defined by the recommendation ITU-T Rec.H.264, Annexe D.9.7, an I image occupies approximately 8 times more memory space than a P image of similar quality. The technical problem posed by compliance with the random access constraint by a video stream or sequence within the framework of the above-mentioned hypothesis can be summarized as follows: if I images are inserted with the aim of complying with the random access constraint, it is necessary to reduce the quality of the latter very substantially in order to avoid exceeding the size of the buffer memories. The resulting quality is then mediocre with, in particular, an especially impeding periodic visual degradation during the passage of reduced-quality I images.
Most recent video encoding standards propose encoding processes making it possible to encode an I image staggered over several P images, called progressive encoding. This new process makes it possible to dispense with the I-image concept.
In practice, each image of the video stream or sequence is subdivided into zones which are successively encoded by blocks in Intraframe mode, while ensuring on the one hand that at the end of a determined number of successive images all the zones of the image will have been encoded in Intra, the I image thus having been distributed over the determined number of images, and on the other hand, that the parts of images encoded in Interframe mode do not use the zone that has not yet been refreshed, in order to retain the information passed from the predictive coding.
In the above-mentioned standard H.264, the video encoder can signal to the video decoder that it is transmitting this type of image with progressive encoding. Thus on reception the video decoder can synchronize on these images, in order to guarantee a random access to the stream. For a more detailed description of the standard H.264 and the progressive encoding process, reference can usefully be made to the text of the above-mentioned recommendation ITU-T Rec.H.264, Annexe D.9.7.
Although the progressive encoding process of I images makes it possible to some extent to comply with a constraint in terms of video image bit rate, while guaranteeing a random access to the video stream, the process of successive encoding of the blocks, according to a geometrical scanning of the image from top to bottom, does not give total satisfaction and does not make it possible to comply with the bit rate constraint with a low margin of error in terms of the target image size.
The bit rate control process in this situation in fact makes use of the computational model, shown and described in connection with FIG. 1b. 
The above-mentioned computational model is affected by a certain absolute error ε, which becomes greater as the estimated size {circumflex over (T)} of the image increases.
Thus the size T of each encoded image verifies the following relationship (1):T={circumflex over (T)}+εin which T denotes the actual size of the image after encoding, {circumflex over (T)} the estimated size of the image given by the computational model and ε the absolute encoding error on the size, a strictly increasing function of the size T.
Taking account of the successive geometrical encoding from top to bottom of the blocks or zones to be encoded, when the bottom of the image, the last zones of the latter to be encoded, has a high complexity, it can be concluded that the absolute size error ε introduced by the computational model is high. In fact, as this zone is encoded last, the absolute error cannot in any way be compensated for by the encoding of other zones, the quality of which could be reduced, for example, in order to reduce the size of the encoded image finally achieved. Consequently this results in a risk of exceeding the capacity of the buffer memories, and degradation of the conditions of transmission, in particular the fluidity of the video stream or sequence.
Currently, no procedures are known that allow fine regulation of the encoding bit rate of video streams or sequences to be carried out while retaining random access to the latter.